Abstract
BackgroundOntologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are now available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal. However, these resources differ substantially in mode, ease of access, and ontology content. This makes it relatively difficult to access each ontology source separately, map their contents to research data, and much of this effort is being replicated across different research groups.ResultsOntoCAT provides a seamless programming interface to query heterogeneous ontology resources including OLS and BioPortal, as well as user-specified local OWL and OBO files. Each resource is wrapped behind easy to learn Java, Bioconductor/R and REST web service commands enabling reuse and integration of ontology software efforts despite variation in technologies. It is also available as a stand-alone MOLGENIS database and a Google App Engine application.ConclusionsOntoCAT provides a robust, configurable solution for accessing ontology terms specified locally and from remote services, is available as a stand-alone tool and has been tested thoroughly in the ArrayExpress, MOLGENIS, EFO and Gen2Phen phenotype use cases.Availabilityhttp://www.ontocat.org
Highlights
Ontologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal
Example use cases of OntoCAT for integrating ontologies with data include: harmonising and promoting consistency in data annotations, facilitating automated annotations, inferring additional information based on the knowledge conceptualisation, supporting complex user queries and user interfaces, nonsense detection and integrating external data
We report successful applications in the following real world scenarios: Figure 3 Use case diagram
Summary
Ontologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal. The Disease Ontology [6] and the NCI Thesaurus [7] are both examples of ontologies in the disease domain and cancer (accession: DOID:162) and Malignant Neoplasm (accession: C9305) are examples of equivalent concepts therein When used this allows for unambiguous attribution of a particular experimental condition or sample characteristic. In recent years the OBO Foundry community has succeeded in creating a valuable catalogue of orthogonal, For the purpose of this article, ontology querying and integration is defined as integration of ontologies into software applications and the practical use of ontologies to annotate real data. This clarification is necessary as ontology integration can be understood as the integration of ontologies when building new ontologies by reusing other ontologies, or integration of ontologies by merging different ontologies into a single one that unifies them [10]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
